Three-Stage Pooled Plasma Hepatitis C Virus RNA Testing for the Identification of Acute HCV Infections in At-Risk Populations

ABSTRACT Timely diagnosis and treatment of hepatitis C virus (HCV) infection may prevent its transmission. We evaluated the performance and cost reductions of the pooled plasma HCV RNA testing strategy to identify acute HCV infections among people living with HIV (PLWH). PLWH with sexually transmitted infections, elevated aminotransferases within the past 6 months or past HCV infections (high-risk) and those without (low-risk) were enrolled prospectively. Participants underwent three-stage pooled plasma HCV RNA testing every 12 to 24 weeks until detection of HCV RNA or completion of a 48-week follow-up. The three-stage strategy combined 20 individual specimens into a stage 1 pool, 5 individual specimens from the stage 1 pool that tested positive for HCV RNA in the stage 2 mini-pool, followed by testing of individual specimens of the stage 2 mini-pool tested positive for HCV RNA. A simulation was constructed to investigate the cost reductions and pooled sensitivity and specificity under different combinations of HCV prevalence and pool/mini-pool sizes. Between June 25, 2019 and March 31, 2021, 32 cases of incident HCV viremia were identified in 760 high-risk PLWH that were enrolled 834 times, giving an incidence rate of 56.6 per 1000 person-years of follow-up (PYFU). No cases of HCV viremia were identified in 557 low-risk PLWH during a total of 269.2 PYFU. Simulation analysis suggested that this strategy could reduce HCV RNA testing cost by 50% to 86% with HCV viremia prevalence of 1% to 5% and various pooled sizes despite compromised pooled sensitivity. This pooled plasma HCV RNA testing strategy is cost-saving to identify acute HCV infections in high-risk populations with HCV viremia prevalence of 1% to 5%. IMPORTANCE Our three-stage pooled plasma HCV RNA testing successfully identified HCV viremia in high-risk PLWH with a testing cost reduction of 84.5%. Simulation analysis offered detailed information regarding the selection of pool and mini-pool sizes in settings of different HCV epidemiology and the performance of HCV RNA testing to optimize the cost reduction.

Then, the required tests for the proposed three-stage pooled testing was 1  = , we must have either 5,1 1  = or 5,2 1  = . Also, if 5,1 0  = , we must have 5,2 1  = . Therefore, the dependence led to the difficulty of deriving derive the statistical characteristics. Alternatively, a simulation of the three-stage pooled testing was applied.
2 Simulation of the three-stage pooled testing Step 1: Generate N indicators (detectable or undetectable) from a Bernoulli distribution with prevalence, say P . If the indicator was 0, then the specimen was denoted by undetectable. In this case, we still assigned a value to this undetectable specimen. Else if the indicator was detectable, then we would randomly select a value from the real detectable database.
Step 2: The simulated three-stage pooled testing was performed; that is, the N specimens were pooled to test. The testing was continued to the second stage with probability of ; otherwise, the testing was continued to the second stage with probability of 1 Sp − ; otherwise, the testing was stopped and the N specimens were considered as undetectable.
Step 3: At the second stage, every k specimens were pooled to test. The testing was continued to the third stage with probability of Se for each subgroup if ; otherwise, the testing was continued to the third stage with probability of 1 Sp − ; otherwise, the subgroup was stopped to test and this k specimens were considered as undetectable.
Step 4: At the third stage, every specimen was tested individually. If the X was greater than c , then the specimen was denoted by detectable with probability of Se ; else if the X was less than c , then the specimen was denoted by detectable with probability of 3 The next section is the R code of the proposed 3-stage pooled strategy. This R code allows user to specify the prevalence, individual sensitivity, individual specificity, N, and k. An additional csv file is required to provide a sample of value of detectable responses. The first row in the csv file is the variable name (can be arbitrary). The following figure is an example of the content: While an example of the output is as following figure:  names(Mytemp) <-c("Prevalence","N","k","Mean","SD","Cost_Reduction", "Test_Sensitivity","Test_Specificity","Prevalence")     Figure S4. Pooled specificity against prevalence with individual sensitivity of 98.94% and individual specificity of 99.99% (Given the detection limit of 15 IU/mL, the value of the undetectable individual specimen is assigned to 0 IU/mL in the left panel, and that of the undetectable individual specimen is assigned to 14 IU/mL in the right panel). For the pooled specificity, all were better than the individual specificity regardless of any HCV viremia prevalence.
31 Figure S5. Cost reduction against prevalence with different lower individual sensitivities (I_Se) and individual specificities (I_Sp) in the setting of the combinations of pooled sizes of (pool size, N = 20, 30, or 40; mini-pool size, k=5) and the value of undetectable individual specimen of 14 IU/mL. The performance remained similar in all settings.
32 Figure S6. Pooled sensitivity against prevalence with different individual sensitivities (I_Se) and individual specificities (I_Sp) in the setting of the combinations of pooled sizes of (pool size, N = 20, 30, or 40; mini-pool size, k=5) and the value of undetectable individual specimen of 14 IU/mL. When the individual sensitivity was 90%, the pooled sensitivity was only around 72%, which was considered poor performance.
33 Figure S7. Pooled specificity against prevalence with different individual sensitivities (I_Se) and individual specificities (I_Sp) in the setting of the combinations of pooled sizes of (pool size, N = 20, 30, or 40; mini-pool size, k=5) and the value of undetectable individual specimen of 14 IU/mL. The pooled specificity decreased with a decrease of individual specificity, but the decrease was acceptable since it was still around 94% even when the HCV viremia prevalence was 20%.